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Pei-Ying Chiang
Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei 106, Taiwan

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Journal article
Published: 12 July 2020 in Sustainability
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Under the vigorous development of global anticipatory computing in recent years, there have been numerous applications of artificial intelligence (AI) in people’s daily lives. Learning analytics of big data can assist students, teachers, and school administrators to gain new knowledge and estimate learning information; in turn, the enhanced education contributes to the rapid development of science and technology. Education is sustainable life learning, as well as the most important promoter of science and technology worldwide. In recent years, a large number of anticipatory computing applications based on AI have promoted the training professional AI talent. As a result, this study aims to design a set of interactive robot-assisted teaching for classroom setting to help students overcoming academic difficulties. Teachers, students, and robots in the classroom can interact with each other through the ARCS motivation model in programming. The proposed method can help students to develop the motivation, relevance, and confidence in learning, thus enhancing their learning effectiveness. The robot, like a teaching assistant, can help students solving problems in the classroom by answering questions and evaluating students’ answers in natural and responsive interactions. The natural interactive responses of the robot are achieved through the use of a database of emotional big data (Google facial expression comparison dataset). The robot is loaded with an emotion recognition system to assess the moods of the students through their expressions and sounds, and then offer corresponding emotional responses. The robot is able to communicate naturally with the students, thereby attracting their attention, triggering their learning motivation, and improving their learning effectiveness.

ACS Style

Yi-Zeng Hsieh; Shih-Syun Lin; Yu-Cin Luo; Yu-Lin Jeng; Shih-Wei Tan; Chao-Rong Chen; Pei-Ying Chiang. ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation. Sustainability 2020, 12, 5605 .

AMA Style

Yi-Zeng Hsieh, Shih-Syun Lin, Yu-Cin Luo, Yu-Lin Jeng, Shih-Wei Tan, Chao-Rong Chen, Pei-Ying Chiang. ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation. Sustainability. 2020; 12 (14):5605.

Chicago/Turabian Style

Yi-Zeng Hsieh; Shih-Syun Lin; Yu-Cin Luo; Yu-Lin Jeng; Shih-Wei Tan; Chao-Rong Chen; Pei-Ying Chiang. 2020. "ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation." Sustainability 12, no. 14: 5605.

Journal article
Published: 01 January 2019 in Journal of Visual Communication and Image Representation
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ACS Style

Pei-Ying Chiang; Chun-Chi Chen; Chih-Hsien Hsia. A touchless interaction interface for observing medical imaging. Journal of Visual Communication and Image Representation 2019, 58, 363 -373.

AMA Style

Pei-Ying Chiang, Chun-Chi Chen, Chih-Hsien Hsia. A touchless interaction interface for observing medical imaging. Journal of Visual Communication and Image Representation. 2019; 58 ():363-373.

Chicago/Turabian Style

Pei-Ying Chiang; Chun-Chi Chen; Chih-Hsien Hsia. 2019. "A touchless interaction interface for observing medical imaging." Journal of Visual Communication and Image Representation 58, no. : 363-373.

Published erratum
Published: 01 July 2018 in Computer Methods and Programs in Biomedicine
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ACS Style

Hung-Jr Shiu; Bor-Sing Lin; Chien-Hung Huang; Pei-Ying Chiang; Chin-Laung Lei. Corrigendum to ``Preserving privacy of online digital physiological signals using blind and reversible steganography'' [Computer Methods and Programs in Biomedicine 151C (2017) 159-170]. Computer Methods and Programs in Biomedicine 2018, 161, 240 .

AMA Style

Hung-Jr Shiu, Bor-Sing Lin, Chien-Hung Huang, Pei-Ying Chiang, Chin-Laung Lei. Corrigendum to ``Preserving privacy of online digital physiological signals using blind and reversible steganography'' [Computer Methods and Programs in Biomedicine 151C (2017) 159-170]. Computer Methods and Programs in Biomedicine. 2018; 161 ():240.

Chicago/Turabian Style

Hung-Jr Shiu; Bor-Sing Lin; Chien-Hung Huang; Pei-Ying Chiang; Chin-Laung Lei. 2018. "Corrigendum to ``Preserving privacy of online digital physiological signals using blind and reversible steganography'' [Computer Methods and Programs in Biomedicine 151C (2017) 159-170]." Computer Methods and Programs in Biomedicine 161, no. : 240.

Original article
Published: 29 June 2018 in Journal of Medical and Biological Engineering
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This study proposes a modular data glove system to accurately and reliably capture hand kinematics. This data glove system’s modular design enhances its flexibility. It can provide the hand’s angular velocities, accelerations, and joint angles to physicians for adjusting rehabilitation treatments. Three validations—raw data verification, static angle verification, and dynamic angle verification—were conducted to verify the reliability and accuracy of the data glove. Furthermore, to ensure the wearability of the data glove, 15 healthy participants and 15 participants with stroke were recruited to test the data glove and fill out a questionnaire. The errors of the finger ROMs obtained from the fusion algorithm were less than 2°, proving that the fusion algorithm can measure the wearer’s range of motion accurately. The result of the questionnaire shows the participants’ high satisfaction with the data glove. Moreover, a comparison between the proposed data glove and related research shows that the proposed data glove is superior to other data glove systems.

ACS Style

Bor-Shing Lin; I-Jung Lee; Pei-Ying Chiang; Shih-Yuan Huang; Chih-Wei Peng. A Modular Data Glove System for Finger and Hand Motion Capture Based on Inertial Sensors. Journal of Medical and Biological Engineering 2018, 39, 532 -540.

AMA Style

Bor-Shing Lin, I-Jung Lee, Pei-Ying Chiang, Shih-Yuan Huang, Chih-Wei Peng. A Modular Data Glove System for Finger and Hand Motion Capture Based on Inertial Sensors. Journal of Medical and Biological Engineering. 2018; 39 (4):532-540.

Chicago/Turabian Style

Bor-Shing Lin; I-Jung Lee; Pei-Ying Chiang; Shih-Yuan Huang; Chih-Wei Peng. 2018. "A Modular Data Glove System for Finger and Hand Motion Capture Based on Inertial Sensors." Journal of Medical and Biological Engineering 39, no. 4: 532-540.

Journal article
Published: 01 June 2018 in IEEE Journal of Biomedical and Health Informatics
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Energy expenditure (EE) monitoring is crucial to tracking physical activity (PA). Accurate EE monitoring may help people engage in adequate activity and therefore avoid obesity and reduce the risk of chronic diseases. This study proposes a depth-camera-based system for EE estimation of PA in gyms. Most previous studies have used inertial measurement units for EE estimation. By contrast, the proposed system can be used to conveniently monitor subjects’ treadmill workouts in gyms without requiring them to wear any devices. A total of 21 subjects were recruited for the experiment. Subjects’ skeletal data acquired using the depth camera and oxygen consumption data simultaneously obtained using the K4b$^{2}$ device was used to establish an EE predictive model. To obtain a robust EE estimation model, depth cameras were placed in the side view, rear side view, and rear view. A comparison of five different predictive models and these three camera locations showed that the multilayer perceptron model was the best predictive model and that placing the camera in the rear view provided the best EE estimation performance. The measured and predicted metabolic equivalents of task exhibited a strong positive correlation, with r = 0.94 and coefficient of determination r$^{2}$ = 0.89. Furthermore, the mean absolute error was 0.61 MET, mean squared error was 0.67 MET, and root mean squared error was 0.76 MET. These results indicate that the proposed system is handy and reliable for monitoring users EE when performing treadmill workouts.

ACS Style

Bor-Shing Lin; Li-Ying Wang; Yi-Ting Hwang; Pei-Ying Chiang; Wei-Jen Chou. Depth-Camera-Based System for Estimating Energy Expenditure of Physical Activities in Gyms. IEEE Journal of Biomedical and Health Informatics 2018, 23, 1086 -1095.

AMA Style

Bor-Shing Lin, Li-Ying Wang, Yi-Ting Hwang, Pei-Ying Chiang, Wei-Jen Chou. Depth-Camera-Based System for Estimating Energy Expenditure of Physical Activities in Gyms. IEEE Journal of Biomedical and Health Informatics. 2018; 23 (3):1086-1095.

Chicago/Turabian Style

Bor-Shing Lin; Li-Ying Wang; Yi-Ting Hwang; Pei-Ying Chiang; Wei-Jen Chou. 2018. "Depth-Camera-Based System for Estimating Energy Expenditure of Physical Activities in Gyms." IEEE Journal of Biomedical and Health Informatics 23, no. 3: 1086-1095.

Article
Published: 23 April 2018 in Multimedia Tools and Applications
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This study aims at enhancing the destination look-up experience based on the fact that humans can easily recognize and remember images and icons of a destination instead of texts and numbers. Thus, this paper propose an algorithm to display buildings in hierarchical publicity and optimize the location distribution and orientation of each buildings. In the usual, the general navigation GPS include a lot of redundant information, and the necessary information always being drowned. Aimed to this point, we build the hierarchical structure according to their consensus-based publicity and spacial relationship to each other. The publicity is approximated by considering transportation importance and consensus visibility which reflects public consideration on metro transportation, opinions on popularity and famousness respectively. In addition to this, consensus-based optimal orientation of icon is optimized for easy recognition according to public preference estimated by clustering the view of public web photos. For the system evaluation, we perform four user studies to verify the effect of recognition and destination searching, and we all get positive response from these user studies.

ACS Style

Pei-Ying Chiang; Shih-Hsuan Hung; Yu-Chi Lai; Chih-Yuan Yao. Destination selection based on consensus-selected landmarks. Multimedia Tools and Applications 2018, 77, 30011 -30033.

AMA Style

Pei-Ying Chiang, Shih-Hsuan Hung, Yu-Chi Lai, Chih-Yuan Yao. Destination selection based on consensus-selected landmarks. Multimedia Tools and Applications. 2018; 77 (22):30011-30033.

Chicago/Turabian Style

Pei-Ying Chiang; Shih-Hsuan Hung; Yu-Chi Lai; Chih-Yuan Yao. 2018. "Destination selection based on consensus-selected landmarks." Multimedia Tools and Applications 77, no. 22: 30011-30033.

Journal article
Published: 01 April 2018 in Journal of Visual Communication and Image Representation
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In this study, an interactive Chinese portrait rendering system was developed. This portrait rendering system can generate a user-lookalike ink portrait by blending the user’s face with a selected Chinese ink painting. It first automatically analyzes the user’s facial features and then integrates them into a selected Chinese painting. This system comprises two processes: an offline process and an online process. During the offline process, a collection of Chinese portrait paintings is configured (e.g., the face masks and facial coordinates of the paintings are determined). Subsequently, blending-ready templates (faces without facial features) are prepared for the online process. During the online process, the user integrates their photograph into our rendering system. The system automatically analyzes the face orientation, color, and facial features and adjusts the attributes of the photograph to match the template’s configuration. The produced facial image is blended into a selected template, which preserves the textures of the original Chinese painting. The results reveal that our system preserved both the user characteristics and original painting styles. In this study, user-portrait matching was experimentally evaluated, and a questionnaire survey on satisfaction with painting style was conducted.

ACS Style

Pei-Ying Chiang; Chun-Von Lin; Cheng-Hua Tseng. Generation of Chinese ink portraits by blending face photographs with Chinese ink paintings. Journal of Visual Communication and Image Representation 2018, 52, 33 -44.

AMA Style

Pei-Ying Chiang, Chun-Von Lin, Cheng-Hua Tseng. Generation of Chinese ink portraits by blending face photographs with Chinese ink paintings. Journal of Visual Communication and Image Representation. 2018; 52 ():33-44.

Chicago/Turabian Style

Pei-Ying Chiang; Chun-Von Lin; Cheng-Hua Tseng. 2018. "Generation of Chinese ink portraits by blending face photographs with Chinese ink paintings." Journal of Visual Communication and Image Representation 52, no. : 33-44.

Original research
Published: 05 February 2018 in Journal of Ambient Intelligence and Humanized Computing
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Volume rendering in real time is limited by the difficulty of creating views for occluded features of interest. This paper presents a novel approach to volume visualization based on a nonlinear distortion model, in which an exploded view of occluded volumetric features is presented in a focus\(+\)context manner. In the proposed system, focus is created using size-based region-growing segmentation. The focus and context can be rendered using various effects to create an intuitive view for the user. In an interactive setting, the proposed technique provides easy visual access to features of interest within a given volume for exploration as well as presentation.

ACS Style

Pei-Ying Chiang; Chun-Yuan Chen. Interactive exploded focus $$+$$ + context technique for volume visualization. Journal of Ambient Intelligence and Humanized Computing 2018, 1 -10.

AMA Style

Pei-Ying Chiang, Chun-Yuan Chen. Interactive exploded focus $$+$$ + context technique for volume visualization. Journal of Ambient Intelligence and Humanized Computing. 2018; ():1-10.

Chicago/Turabian Style

Pei-Ying Chiang; Chun-Yuan Chen. 2018. "Interactive exploded focus $$+$$ + context technique for volume visualization." Journal of Ambient Intelligence and Humanized Computing , no. : 1-10.

Journal article
Published: 01 November 2017 in Computer Methods and Programs in Biomedicine
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Physiological signals such as electrocardiograms (ECG) and electromyograms (EMG) are widely used to diagnose diseases. Presently, the Internet offers numerous cloud storage services which enable digital physiological signals to be uploaded for convenient access and use. Numerous online databases of medical signals have been built. The data in them must be processed in a manner that preserves patients' confidentiality.A reversible error-correcting-coding strategy will be adopted to transform digital physiological signals into a new bit-stream that uses a matrix in which is embedded the Hamming code to pass secret messages or private information. The shared keys are the matrix and the version of the Hamming code.An online open database, the MIT-BIH arrhythmia database, was used to test the proposed algorithms. The time-complexity, capacity and robustness are evaluated. Comparisons of several evaluations subject to related work are also proposed.This work proposes a reversible, low-payload steganographic scheme for preserving the privacy of physiological signals. An (n, m)-hamming code is used to insert (n - m) secret bits into n bits of a cover signal. The number of embedded bits per modification is higher than in comparable methods, and the computational power is efficient and the scheme is secure. Unlike other Hamming-code based schemes, the proposed scheme is both reversible and blind.

ACS Style

Hung-Jr Shiu; Bor-Sing Lin; Chien-Hung Huang; Pei-Ying Chiang; Chin-Laung Lei. Preserving privacy of online digital physiological signals using blind and reversible steganography. Computer Methods and Programs in Biomedicine 2017, 151, 159 -170.

AMA Style

Hung-Jr Shiu, Bor-Sing Lin, Chien-Hung Huang, Pei-Ying Chiang, Chin-Laung Lei. Preserving privacy of online digital physiological signals using blind and reversible steganography. Computer Methods and Programs in Biomedicine. 2017; 151 ():159-170.

Chicago/Turabian Style

Hung-Jr Shiu; Bor-Sing Lin; Chien-Hung Huang; Pei-Ying Chiang; Chin-Laung Lei. 2017. "Preserving privacy of online digital physiological signals using blind and reversible steganography." Computer Methods and Programs in Biomedicine 151, no. : 159-170.

Journal article
Published: 13 June 2017 in Sensors
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Visually impaired people are often unaware of dangers in front of them, even in familiar environments. Furthermore, in unfamiliar environments, such people require guidance to reduce the risk of colliding with obstacles. This study proposes a simple smartphone-based guiding system for solving the navigation problems for visually impaired people and achieving obstacle avoidance to enable visually impaired people to travel smoothly from a beginning point to a destination with greater awareness of their surroundings. In this study, a computer image recognition system and smartphone application were integrated to form a simple assisted guiding system. Two operating modes, online mode and offline mode, can be chosen depending on network availability. When the system begins to operate, the smartphone captures the scene in front of the user and sends the captured images to the backend server to be processed. The backend server uses the faster region convolutional neural network algorithm or the you only look once algorithm to recognize multiple obstacles in every image, and it subsequently sends the results back to the smartphone. The results of obstacle recognition in this study reached 60%, which is sufficient for assisting visually impaired people in realizing the types and locations of obstacles around them.

ACS Style

Bor-Shing Lin; Cheng-Che Lee; Pei-Ying Chiang. Simple Smartphone-Based Guiding System for Visually Impaired People. Sensors 2017, 17, 1371 .

AMA Style

Bor-Shing Lin, Cheng-Che Lee, Pei-Ying Chiang. Simple Smartphone-Based Guiding System for Visually Impaired People. Sensors. 2017; 17 (6):1371.

Chicago/Turabian Style

Bor-Shing Lin; Cheng-Che Lee; Pei-Ying Chiang. 2017. "Simple Smartphone-Based Guiding System for Visually Impaired People." Sensors 17, no. 6: 1371.